| Hector R. Gavilanes | Chief Information Officer |
| Gail Han | Chief Operating Officer |
| Michael T. Mezzano | Chief Technology Officer |
University of West Florida
November 2023
The prcomp() function performs principal component analysis on a dataset using the singular value decomposition method with the covariance matrix of the data.
Driven by multicollinearity.
Features less significant in explaining variability.
All variables are numeric
Categorical Index variable.
34 missing values.
Imputation of missing values using the \(Mean\) (\(\mu\))
Mean (\(\mu\)=0); Standard Deviation (\(\sigma\)= 1)
\[ Z = \frac{{ x - \mu }}{{ \sigma }} \]
\[ Z \sim N(0,1) \]
3 Outliers
No leverage
Minimal difference.
No observations removed.